Method for remediating developmentally delayed plants

ABSTRACT

A method for remediating developmentally delayed plants within a field of crops using at least one work vehicle during a field operation. The method comprises identifying delayed plants within the field with a sensor on the work vehicle and generating, with a processor, location data associated with the location of the delayed plant with the field. Upon arriving at the location of the delayed plant with the work vehicle, the delayed plant is remediated.

FIELD OF THE DISCLOSURE

The present disclosure relates generally to a method for remediatingdevelopmentally delayed crop plants within a field of growing crops.

BACKGROUND OF THE DISCLOSURE

The problem of developmentally delayed crops—for example corn plantsemerging significantly later than surrounding corn plants—is well known.Delayed plants use water, nutrients, and sunlight without producing aproportional amount of grain. By remediating delayed plants, theremaining crop plants have more resources with which to be productive.

SUMMARY OF THE DISCLOSURE

According to an aspect of the present disclosure, a method is providedfor remediating developmentally delayed plants within a field of cropsusing at least one work vehicle. The method comprises identifyingdelayed plants within the field with a sensor on the work vehicle andgenerating, with a processor, location data associated with the locationof the delayed plant with the field. Upon arriving at the location ofthe delayed plant within the field with the work vehicle, the delayedplant is remediated.

According to another aspect of the present disclosure, a method isprovided for remediating developmentally delayed plants within a fieldwith at least one work vehicle. The method comprises identifying, with aprocessor, a delayed plant using agricultural data for the field;generating, with the processor, location data associated with thelocation of the delayed plant within the field; and storing the locationdata. The delayed plant may then be located during a field operationusing the stored location data and a sensor on a work vehicle and, uponlocating the delayed plant, remediated,

According to yet another aspect of the present disclosure, a method isprovided for remediating developmentally delayed plants within a fieldof crops using at least one work vehicle. The method comprisesidentifying delayed plants within the field with a sensor on a workvehicle; determining, with a processor, a delay amount for at least onedelayed plant; and comparing, with the processor, the amount of delayagainst at least one delay development threshold. The plant isremediated if the amount of delay relative to the at least one delaydevelopment threshold

Other features and aspects will become apparent by consideration of thedetailed description and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description of the drawings refers to the accompanyingfigures in which:

FIG. 1 is a schematic representation of a method for remediating delayedplants;

FIG. 2 is a schematic representation of a plant remediating device forremediating delayed plants;

FIG. 3 is a schematic representation of a method for remediating delayedplants using at least one crop emergence map; and

FIG. 4 is a schematic representation of a method for remediating delayedplants using economic information associated with the plant remediatingactivity.

DETAILED DESCRIPTION OF THE DRAWINGS

Referring now to FIG. 1, a schematic representation of a method forremediating delayed plants is shown. In Step 1000, delayed plants on aworksite (e.g., a field) are identified and data is generated associatedwith a single delayed plant, groups of plants or some combinationthereof. The generated data may then be transmitted as a set ofgeographic coordinates at either or both global and local levels orother similar representation to another work vehicle or stored on adatabase for subsequent retrieval. This identification may occur in realtime 1010, using emergence date data 1020, using as-planted data 1030,or any other suitable means 1040.

For example, as shown by Step 1100, one or more sensors mounted to awork vehicle are used to identify a delayed plant during a fieldoperation. The work vehicle is at least one vehicle and, in one specificexample, is a first work vehicle and a second work vehicle. The firstand second work vehicles are typically, without limitation, any of thefollowing: a self-propelled sprayer, a high clearance sprayer, atractor-mounted sprayer, a tractor and towed implement such as acultivator or fertilizer applicator, a UAV, airplane, utility vehicle,or a small terrestrial robot. The field operation may involve spraying acrop, planting, cultivating, aerial observation, crop scouting or anyother operation customarily performed with a crop.

In one example, when the output of Step 1000 is agricultural data suchas map having the global or local geographic coordinates of delayedplants, a Global Navigation Satellite System 1110 sensor is used tolocate the work vehicle during a field operation relative to one or moredelayed plants on the worksite. Location data corresponding to thelocation of the delayed plant is generated by a processor using thesignal from sensor 1110 and, in one example, transmitted to a databaseor to another work vehicle.

However, when the relative plant development is being measured inreal-time during a field operation as the work vehicle moves through thefield, the sensor may be a camera 1120 or other suitable sensor 1130 andagain location data is generated by a processor using the signal fromsensors 1120 or 1130. In this example, the camera 1120 may generated animage of the delayed plant from which location data is generated. Thelocation data of the delayed plant may be the centroid of the delayedplant derived from the image and the coordinates at which a plantremediator is actuated. In Step 1200, one or more identified delayedplants are killed by a plant remediator on the work vehicle using thedata generated during the identification of the delayed plants of Step1000, The plant remediator may be a chemical or hot liquid spray 1210, amechanical “hoe” 1220, or any other plant killing means 1230.

Referring now to FIG. 2, an example embodiment 2000 which can performthe real-time method of FIG. 1 is shown. With respect to Step 1000,real-time plant sensors 2100 may include, alone or in combination, thefollowing: camera 2110, stereo camera 2120, acoustic sensor 2130, LIDAR2140, structured light sensor 2150, or other sensors 2160. Processor2200 receives data about plants on a portion of worksite 2400 fromreal-time plant sensors 2100 and generates at least informationconcerning location of the delayed plants relative to the work vehicleon worksite 2400. In another example, processor 2200 generatesinformation concerning the amount of delay for an individual plant or agroup of plants.

Developmental delay, including the amount of delay of an individual orgroup of plants, may be assessed on a single factor or multiple factorsincluding, without limitation: time of emergence, growth stage, plantheight, leaf count, leaf area index, plant volume, stalk diameter,shattering, lodging and reflectance spectra. Delay may be expressed inabsolute terms, e.g., growth stage V4, or relative to a set of plants,e.g., 10th percentile of emergence. Based on a delay developmentthreshold 2210, plants are classified as normal plants 2410 or delayedplants 2420 in Step 1100. The delay development threshold may bedetermined manually by a user; calculated in part with user-providedagricultural data and also in part using processor 2200; or,alternatively, the threshold may be calculated and/or modeled entirelyby the processor 2200 using agricultural data from one or more databaseswithout input or with only confirmation input from the user. Forexample, a user may provide a delay development threshold afterconsulting with his or her agronomist. Alternatively, a user may provideonly agricultural data in the form of an as-planted map while relying onthe processor and associated real-time sensors to provide otheragricultural data relating to emergence to determine the amount of delayand/or the delay development threshold.

Plants identified as being delayed or otherwise not meeting threshold2210 are remediated by plant remediators 2300 in Step 1200. Plantremediators 2300 may include without limitation chemical sprays 2310,thermal sprays 2320 such as hot oil or liquid nitrogen, a mechanicalhoe, cutter, or flail 2330, an optical means 2340 such as a laser, orany other suitable means. However, it can be appreciated by one ofordinary skill that instead of killing the delayed plant, Step 1200 maybe adapted to involve plant growth stimulation using fertilizers, plantgrowth regulators, or soil amendments. In general, any treatment whichcauses a plant to grow at a faster rate than an untreated plant may beused.

In one example, stimulation may be accomplished through a foliarapplication of a plant growth regulator such as Ascend® SL sold byWinfield United. For example, when a delayed plant is identified, Step1100 may generate data regarding the amount of the delay. If the amountof delay is determined to be minimal or otherwise not meet the delaydevelopment threshold 2210, the plant could be stimulated to catch up tosurrounding plants or left alone entirely. In some examples, a seconddelay development threshold 221 x may be present. If the delay fails tomeet (first) delay development threshold 2210, then the plant iseliminated. If the plant exceeds (first) delay development threshold2210 but not second delay development threshold 221 x, it is stimulated.Otherwise the plant is left to continue growing as is. It can beappreciated that any number of delay development thresholds may be usedto remediate—through elimination, stimulation or otherwise—a delayedplant.

In one example, the processor 2200 may be comprised of one or more ofsoftware and/or hardware in any proportion. In such an example, theprocessor 2200 may reside on a computer-based platform such as, forexample, a server or set of servers. Any such server or servers may be aphysical server(s) or a virtual machine(s) executing on another hardwareplatform or platforms. Any server, or for that matter any computer-basedsystem, systems or elements described herein, will be generallycharacterized by one or more processors and associated processingelements and storage devices communicatively interconnected to oneanother by one or more busses or other communication mechanism forcommunicating information or data. In one example, storage within suchdevices may include a main memory such as, for example, a random accessmemory (RAM) or other dynamic storage devices, for storing informationand instructions to be executed by the processor(s) and for storingtemporary variables or other intermediate information during the use ofthe system and computing element described herein.

In one example, the processor 2200 may also include a static storagedevice such as, for example, read only memory (ROM), for storing staticinformation and instructions for the processor(s). In one example, theprocessor 2200 may include a storage device such as, for example, a harddisk or solid state memory, for storing information and instructions.Such storing information and instructions may include, but not belimited to, instructions to compute, which may include, but not belimited to processing and analyzing agronomic data or information of alltypes. Such data or information may pertain to, but not be limited to,weather, soil, water, crop growth stage, pest or disease infestationdata, historical data, future forecast data, economic data associatedwith agronomics or any other type of agronomic data or information.

In one example, the processing and analyzing of data by the processor2200 may pertain to processing and analyzing agronomic factors obtainedfrom externally gathered image data, and issue alerts if so requiredbased on pre-defined acceptability parameters. RAMS, ROMs, hard disks,solid state memories, and the like, are all examples of tangiblecomputer readable media, which may be used to store instructions whichcomprise processes, methods and functionalities of the presentdisclosure. Exemplary processes, methods and functionalities of theprocessor 2200 may include determining a necessity for generating andpresenting alerts in accordance with examples of the present disclosure.Execution of such instructions causes the various computer-basedelements of processor 2200 to perform the processes, methods,functionalities, operations, etc., described herein. In some examples,the processor 2200 of the present disclosure may include hard-wiredcircuitry to be used in place of or in combination with, in anyproportion, such computer-readable instructions to implement thedisclosure.

FIG. 3 shows an example embodiment 3000 which can perform the method ofFIG. 1 using various a priori agricultural data such as planting andenvironmental information. The various agricultural data may be storedon a plurality of databases or database servers. In one example, thedatabases store a variety of planting and environmental information andadditionally perform calculations and/or other functionality. Any numberof databases may be included and relate to specific first agriculturaldata, second agricultural data or multiple sets of agricultural data.For example, agricultural data may relate to as-planted map 3110 or,alternatively, first agricultural data and second agricultural datacorresponding, respectively, to a first crop emergence map 3120 and asecond crop emergence map 3130 stored on the same database or differentdatabases. Moreover, the agricultural data may have temporal differencessuch as, for example, a first crop emergence map acquired at a differenttime than the second crop emergence map using a camera mounted on aterrestrial vehicle or aerial vehicle traveling across or near worksite2400. In some examples there are only two crop emergence maps; however,it can be appreciated that a plurality of emergence maps may be used togenerate development delay data and thresholds.

As mentioned above, the agricultural data may be an as-planted map 3110acquired using planter seed location placement data generated prior toor during planting of a crop.

As-planted map 3110 shows locations of seeds or future plants 3112 a-f.At some time after planting, the first emergence map 3120 is generatedshowing plants 3112 a,c,d,e have emerged as depicted by the filled incircles. In practice, this may be based on detecting a sufficient amountof “green” at an expected seed location such as recorded in as-plantedmap 3110. At some time interval later, a second emergence map 3130 isgenerated showing that plant 3112 b has emerged, but plant 3112 f isstill absent. This situation corresponds to FIG. 2 depicting normalplants 2410, delayed plant 2420, and missing plant 2430.

Accordingly, first emergence map 3120 and second emergence map 3130 maybe collected at regular time intervals or at other intervals calculatedin part with environmental data 3140 such as weather 3142, worksitetopography 3144, soil temperature 3146, growing degree days 3148 or anyother environmental information 3150. For example, rather thanseparating the intervals by time such as hours or days, the images maybe separated by growing degree days 3148.

Growing degree days 3148 provides a heuristic tool useful in determiningwhen a plant will reach various growth stages and expected water andnutrient usage. Growing degree days 3148 may account for aspects oflocal weather and predict a plant's pace towards maturity. Unlessstressed by other agronomic factors, like moisture, the development ratefrom emergence to maturity for many plants may depend upon the daily airor soil temperature. For example, the growing degrees days on the sunnysouth side of a hill may vary from that on the less directly sunlitnorthern side. Growing degree days may be defined as a number oftemperature degrees above a certain threshold base temperature, whichvaries among plant species, below which plant growth is zero or almostzero. Thus, the intervals on which to collect agricultural data, such asthe first emergence map 3120 and second emergence map 3130, may be basedon the accumulation of growing degree days during the vegetative statesor reproductive states of the crop.

It is known that significant yield loss can occur when emergence ofplants within a stand are delayed. See, e.g., Ford, J. H. and D. R.Hicks. 1992, Corn growth and yield in uneven emerging stands, J. ofProduction Agriculture, 5:185-188; Liu, W., Tollenaar, M., Stewart, G.and Dean, W, 2004, Response of corn grain yield to spatial and temporalvariability in emergence, Crop Sci, 44:847-854; and Heiniger, R. W. andL. Boerema, 2015, How important is uniform emergence in corn, In 2015,Agronomy Abstracts, ASA. The foregoing references, all of which areincorporated reference, provide guidance on establishing delaydevelopment thresholds 2210, 221 x, 3210 and 321 x. For example, thefollowing limitations may be used when evaluating emergence of cornplants:

a. More than 48 hours delayed after 50% of planted seeds have emerged

b. More than 24 hours delayed after 70% of planted seeds within 5 metershave merged

c. More than 25 growing degree days after 8 adjacent plants have emerged

FIG. 4 shows an example method 4000 for improving the economics of themethod shown in FIG. 1 by only performing the plant remediation step1200 in portions of worksite 2400 where the estimated benefit of theactivity exceeds the cost. In Step 4100. delayed plants are identifiedusing agricultural data acquired and stored as described with FIG. 3.Referring to Step 4200, traversable segments on worksite 2400 areidentified. In a stereotypical field, this would be work vehicle passesfrom headland to headland. Also in stereotypical fields, these passescould be modified by waterways or other features.

Now referring to step 4300 of FIG. 4, the difference between the valueof estimated benefit from remediating delayed plants and the cost oftraversing the segment and remediating delayed plants is calculated foreach segment. The value may be positive or negative and may bedetermined by relying on economic indicators or variables, either inpart or in whole. For example, the values may correspond to a highestcrop yield at a lowest cost. In this example, the costs are associatedwith a wide variety of factors, variables, and steps during the growthprocess. Some of the possible costs associated with the growth processinclude, but are not limited to, input costs from, for example, seeds,nitrogen, irrigation, pesticides, etc.; fuel charges; labor costs; etc.Additionally, the estimated benefit from remediating delayed plant maybe derived from other economic factors such as, for example, expectedgain in bushels per acre or plant; expected loss in bushels per acre orplant; break even costs; various cost breakdowns of inputs (e.g.,nitrogen cost per pass in zone/field, cost of a unit of measure ofnitrogen (e.g., pound, etc.), fuel efficiency, etc.); or a wide varietyof other factors.

Further referring to FIG. 4, in Step 4400 the sum of segments withpositive value is compared to fixed economic costs of treating the fieldsuch as mileage and wages to get from a starting point to the field andback. If the result is negative, then it isn't worth treating the fieldand the method ends. If the result is positive, or greater than athreshold value, execution proceeds to Step 4500 where the positivevalue segments and any necessary negative value segments are used togenerate a path and treatment plan. This plan is carried out by a workvehicle in Step 4600.

In the examples of the method of FIG. 4, the steps are carried out usingseveral candidate work vehicles such as, without limitation, a 90 footwide self- propelled sprayer, a narrow high clearance sprayer, a narrowtractor-mounted sprayer, a UAV, or a small terrestrial robot. Each workvehicle and associated field operation has its own economics and pathplan. Thus the decision is not only if a field should be treated and ifso, which segments or passes, but also with which work vehicle. The workvehicle may be selected based on one or more criteria such as lowestcost, earliest mission completion (such as due to worksiteaccessibility, equipment availability, etc.).

Those having skill in the art will recognize that the state of the arthas progressed to the point where there is little distinction leftbetween hardware and software implementations of aspects of systems; theuse of hardware or software is generally (but not always, in that incertain contexts the choice between hardware and software can becomesignificant) a design choice representing cost vs. efficiency tradeoffs.Those having skill in the art will appreciate that there are variousvehicles by which processes and/or systems and/or other technologiesdescribed herein can be effected (e.g., hardware, software, and/orfirmware), and that the preferred vehicle will vary with the context inwhich the processes and/or systems and/or other technologies aredeployed. For example, if an implementer determines that speed andaccuracy are paramount, the implementer may opt for a mainly hardwareand/or firmware vehicle; alternatively, if flexibility is paramount, theimplementer may opt for a mainly software implementation; or, yet againalternatively, the implementer may opt for some combination of hardware,software, and/or firmware. Hence, there are several possible vehicles bywhich the systems, methods, processes, apparatuses and/or devices and/orother technologies described herein may be effected, none of which isinherently superior to the other in that any vehicle to be utilized is achoice dependent upon the context in which the vehicle will be deployedand the specific concerns (e.g., speed, flexibility, or predictability)of the implementer, any of which may vary.

The foregoing detailed description has set forth various embodiments ofthe systems, apparatuses, devices, methods and/or processes via the useof block diagrams, schematics, flowcharts, examples and/or functionallanguage. Insofar as such block diagrams, schematics, flowcharts,examples and/or functional language contain one or more functions and/oroperations, it will be understood by those within the art that eachfunction and/or operation within such block diagrams, schematics,flowcharts, examples or functional language can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, or virtually any combination thereof. In one example, severalportions of the subject matter described herein may be implemented viaApplication Specific Integrated Circuits (ASICs), Field ProgrammableGate Arrays (FPGAs), digital signal processors (DSPs), or otherintegrated formats. However, those skilled in the art will recognizethat some aspects of the embodiments disclosed herein, in whole or inpart, can be equivalently implemented in integrated circuits, as one ormore computer programs running on one or more computers (e.g., as one ormore programs running on one or more computer systems), as one or moreprograms running on one or more processors (e.g., as one or moreprograms running on one or more microprocessors), as firmware, or asvirtually any combination thereof, and that designing the circuitryand/or writing the code for the software and or firmware would be wellwithin the skill of one of skill in the art in light of this disclosure.In addition, those skilled in the art will appreciate that themechanisms of the subject matter described herein are capable of beingdistributed as a program product in a variety of forms, and that anillustrative embodiment of the subject matter described herein appliesregardless of the particular type of signal bearing medium used toactually carry out the distribution. Examples of a signal bearing mediuminclude, but are not limited to, the following: a computer readablememory medium such as a magnetic medium like a floppy disk, a hard diskdrive, and magnetic tape; an optical medium like a Compact Disc (CD), aDigital Video Disk (DVD), and a Blu-ray Disc; computer memory likerandom access memory (RAM), flash memory, and read only memory (ROM);and a transmission type medium such as a digital and/or an analogcommunication medium like a fiber optic cable, a waveguide, a wiredcommunications link, and a wireless communication link.

The herein described subject matter sometimes illustrates differentcomponents associated with, comprised of, contained within or connectedwith different other components. It is to be understood that suchdepicted architectures are merely exemplary, and that in fact many otherarchitectures can be implemented which achieve the same functionality.In a conceptual sense, any arrangement of components to achieve the samefunctionality is effectively “associated” such that the desiredfunctionality is achieved. Hence, any two or more components hereincombined to achieve a particular functionality can be seen as“associated with” each other such that the desired functionality isachieved, irrespective of architectures or intermediate components.Likewise, any two or more components so associated can also be viewed asbeing “operably connected”, or “operably coupled”, to each other toachieve the desired functionality, and any two or more componentscapable of being so associated can also be viewed as being “operablycouplable”, to each other to achieve the desired functionality. Specificexamples of operably couplable include, but are not limited to,physically mateable and/or physically interacting components, and/orwirelessly interactable and/or wirelessly interacting components, and/orlogically interacting and/or logically interactable components.

Unless specifically stated otherwise or as apparent from the descriptionherein, it is appreciated that throughout the present disclosure,discussions utilizing terms such as “accessing,” “aggregating,”“analyzing,” “applying,” “brokering,” “calibrating,” “checking,”“combining,” “communicating,” “comparing,” “conveying,” “converting,”“correlating,” “creating,” “defining,” “deriving,” “detecting,”“disabling,” “determining,” “enabling,” “estimating,” “filtering,”“finding,” “generating,” “identifying,” “incorporating,” “initiating,”“locating,” “modifying,” “obtaining,” “outputting,” “predicting,”“receiving,” “reporting,” “retrieving,” “sending,” “sensing,” “storing,”“transforming,” “updating,” “using,” “validating,” or the like, or otherconjugation forms of these terms and like terms, refer to the actionsand processes of a computer system or computing element (or portionthereof) such as, but not limited to, one or more or some combinationof: a visual organizer system, a request generator, an Internet coupledcomputing device, a computer server, etc. In one example, the computersystem and/or the computing element may manipulate and transforminformation and/or data represented as physical (electronic) quantitieswithin the computer system's and/or computing element's processor(s),register(s), and/or memory(ies) into other data similarly represented asphysical quantities within the computer system's and/or computingelement's memory(ies), register(s) and/or other such informationstorage, processing, transmission, and/or display components of thecomputer system(s), computing element(s) and/or other electroniccomputing device(s). Under the direction of computer-readableinstructions, the computer system(s) and/or computing element(s) maycarry out operations of one or more of the processes, methods and/orfunctionalities of the present disclosure.

Those skilled in the art will recognize that it is common within the artto implement apparatuses and/or devices and/or processes and/or systemsin the fashion(s) set forth herein, and thereafter use engineeringand/or business practices to integrate such implemented apparatusesand/or devices and/or processes and/or systems into more comprehensiveapparatuses and/or devices and/or processes and/or systems. That is, atleast a portion of the apparatuses and/or devices and/or processesand/or systems described herein can be integrated into comprehensiveapparatuses and/or devices and/or processes and/or systems via areasonable amount of experimentation.

Although the present disclosure has been described in terms of specificembodiments and applications, persons skilled in the art can, in lightof this teaching, generate additional embodiments without exceeding thescope or departing from the spirit of the present disclosure describedherein. Accordingly, it is to be understood that the drawings anddescription in this disclosure are proffered to facilitate comprehensionof the present disclosure, and should not be construed to limit thescope thereof.

What is claimed is:
 1. An apparatus comprising: at least one memory;instructions; and a processor to execute the instructions to: identify adevelopmentally delayed plant within a field based on information from asensor, generate location data corresponding to a location of thedevelopmentally delayed plant, and store the location data forremediation of the developmentally delayed plant.
 2. The apparatus ofclaim 1, wherein the processor is a first processor of a first workvehicle, and wherein the instructions cause the first processor tocommunicate the location data to a second processor of a second workvehicle, the second processor to execute second instructions stored in asecond memory to cause, upon arriving at the location of thedevelopmentally delayed plant with the second work vehicle, remediationof the developmentally delayed plant with a plant remediator.
 3. Theapparatus of claim 1, wherein the processor is a first processor of afirst work vehicle, and wherein the instructions cause the firstprocessor to communicate second instructions to a second processor of asecond work vehicle, the second processor to execute the secondinstructions to cause remediation of the developmentally delayed plantwith a plant remediator during a subsequent field operation with thesecond work vehicle.
 4. The apparatus of claim 1, further including alaser to remediate the developmentally delayed plant.
 5. The apparatusof claim 1, wherein the location data is at least one of a localgeographic coordinate or a global geographic coordinate associated withthe developmentally delayed plant.
 6. The apparatus of claim 1, whereinthe instructions cause the processor to: determine an amount of delay ofthe developmentally delayed plant; and compare the amount of delayagainst a delay development threshold.
 7. The apparatus of claim 6,wherein the instructions cause the processor to operate a plantremediator if the amount of delay does not meet the delay developmentthreshold.
 8. An apparatus comprising: a sensor; a laser; and processorcircuitry communicatively coupled to the sensor and the laser, theprocessor circuitry to: determine a location of a plant requiringremediation based on stored location data and information from thesensor, the stored location data associated with the location of theplant requiring remediation within a field identified using agriculturaldata, and cause the laser to remediate the plant requiring remediationbased on the location.
 9. The apparatus of claim 8, further including atleast one memory, wherein the processor circuitry is to retrieve theagricultural data from the at least one memory.
 10. The apparatus ofclaim 9, wherein the agricultural data is at least one of an as-plantedmap, a first crop emergence map or a second crop emergence map for thefield.
 11. The apparatus of claim 8, wherein the processor circuitry isto identify the plant requiring remediation prior to a field operation.12. The apparatus of claim 8, wherein the processor circuitry is tocause transmission of an instruction to a second work vehicle, theinstruction to indicate to the second work vehicle to eliminate theplant requiring remediation.
 13. The apparatus of claim 8, furtherincluding at least one of a chemical spray, thermal spray, mechanicalhoe, cutter, or flail.
 14. The apparatus of claim 8, wherein the sensoris a camera, and wherein the processor circuitry is to determine thelocation of the plant requiring remediation based on image data from thecamera.
 15. A computer readable medium comprising instructions, which,when executed, cause at least one processor to: identify, with a sensoron a work vehicle, at least one developmentally delayed plant within afield; generate location data corresponding to a location of the atleast one developmentally delayed plant; and store the location data forremediation of the at least one developmentally delayed plant.
 16. Thecomputer readable medium of claim 15, wherein the instructions cause theat least one processor to cause a laser to emit a laser beam toward theat least one developmentally delayed plant.
 17. The computer readablemedium of claim 15, wherein the instructions cause the at least oneprocessor to: calculate a cost of eliminating the at least onedevelopmentally delayed plant; calculate an expected benefit ofeliminating the at least one developmentally delayed plant; and if theexpected benefit exceeds the cost, eliminate the at least onedevelopmentally delayed plant.
 18. The computer readable medium of claim17, wherein the instructions cause the at least one processor tocalculate the expected benefit using a change in crop yield for thefield subsequent to elimination of the at least one developmentallydelayed plant.
 19. The computer readable medium of claim 15, wherein theinstructions cause the at least one processor to: compare a delay amountof the at least one developmentally delayed plant against a first delaydevelopment threshold and a second delay development threshold; cause aplant remediator to eliminate the at least one developmentally delayedplant if the delay amount does not meet the first delay developmentthreshold; and cause application of a stimulant to the at least onedevelopmentally delayed plant if the delay amount meets the first delaydevelopment threshold but does not meet the second delay developmentthreshold.
 20. The computer readable medium of claim 15, wherein thework vehicle is a first work vehicle, and wherein the instructions causethe at least one processor to cause a plant remediator to eliminate theat least one developmentally delayed plant by transmitting aninstruction to a second work vehicle, the instruction to indicate to thesecond work vehicle to eliminate the at least one developmentallydelayed plant.